MEXICO: A study recently published in the journal proceedings of the National Academy of Sciences reveals that throughout history, there appears to be a deep imprint of universal positivity bias in the words of natural human language, suggesting that the most commonly used words are more likely to carry positive connotations regardless of culture and origin.
An international team of researchers, composed of mathematicians, modelers, and linguists led by Peter Sheridan Dodds of the University of Vermont, was necessary to conduct the largest-ever study of natural language and its emotional capacity, which focused on confirming the Pollyanna hypothesis.
The LA Times reports that the new research is the first to use “big data” to confirm this hypothesis, which states that human communication will generally skew towards happy, since humans are fundamentally happiest when socializing. The Pollyanna hypothesis was first introduced in 1969 and proposes that compared to negative words, humans would be more expected to use words that convey positive emotions to be “more prevalent, more meaningful, more diversely used and more readily learned,” wrote the authors.
Using human evaluation of 100,000 words across 24 corpora in 10 languages, diverse in origin and culture, the team managed to generate lists of the roughly 10,000 most frequently used words in each of the 10 languages, which included English, Spanish, French, German, Brazilian Portuguese, Korean, Chinese, Russian, Indonesian, and Egyptian Arabic.
Native-speaking volunteers were then asked to rate how they felt in response to each word on a nine-point scale, with 1 being the most negative and 9 being the most positive. Each word collected 50 ratings from native speakers. From this method, the researchers found that in general, each language uses positive words more frequently and in a wider range of forms.
While the study is the largest conducted of its kind and the first to use big data, the researchers do have suggestions for future studies. These include utilizing new languages, different demographic groups, and including phrases instead of just words.
MEXICO: A study recently published in the journal Proceedings of the National Academy of Sciences reveals that throughout history, there appears to be a deep imprint of universal positivity bias in the words of natural human language, suggesting that the most commonly used words are more likely to carry positive connotations regardless of culture and origin.
An international team of researchers, composed of mathematicians, modelers, and linguists led by Peter Sheridan Dodds of the University of Vermont, was necessary to conduct the largest-ever study of natural language and its emotional capacity, which focused on confirming the Pollyanna hypothesis.
The LA Times reports that the new research is the first to use “big data” to confirm this hypothesis, which states that human communication will generally skew towards happy, since humans are fundamentally happiest when socializing. The Pollyanna hypothesis was first introduced in 1969 and proposes that compared to negative words, humans would be more expected to use words that convey positive emotions to be “more prevalent, more meaningful, more diversely used and more readily learned,” wrote the authors.
Using human evaluation of 100,000 words across 24 corpora in 10 languages, diverse in origin and culture, the team managed to generate lists of the roughly 10,000 most frequently used words in each of the 10 languages, which included English, Spanish, French, German, Brazilian Portuguese, Korean, Chinese, Russian, Indonesian, and Egyptian Arabic.
Native-speaking volunteers were then asked to rate how they felt in response to each word on a nine-point scale, with 1 being the most negative and 9 being the most positive. Each word collected 50 ratings from native speakers. From this method, the researchers found that in general, each language uses positive words more frequently and in a wider range of forms.
While the study is the largest conducted of its kind and the first to use big data, the researchers do have suggestions for future studies. These include utilizing new languages, different demographic groups, and including phrases instead of just words.
